2019
Deep Learning Features for Robust Detection of Acoustic Events in Sleep-disordered Breathing
ICASSP 2019accepted
Sleep-disordered breathing (SDB) is a serious and prevalent condition, and acoustic analysis via consumer devices (e.g. smartphones) offers a low-cost solution to screening for it. We present a novel approach for the acoustic identification of SDB sounds, such as snoring, using bottleneck features l…